Bayesian Computation Statistics
A Comparative Study of RPEL and JPEL for Parameter Estimation

Mahdieh Bayati

Volume 2, Issue 2 , June 2024, , Pages 103-118

https://doi.org/10.22054/jdsm.2025.82838.1058

Abstract
  This study generalizes the joint empirical likelihood (JEL) which is named the joint penalized empirical likelihood(JPEL) and presents a comparative analysis of two innovative empirical likelihood methods: the restricted penalized empirical likelihood (RPEL) and the joint penalized empirical likelihood. ...  Read More

Bayesian Network
A Simple Gibbs Sampler for Learning Bayesian Network Structure

Vahid Rezaei Tabar

Volume 1, Issue 2 , June 2023, , Pages 87-97

https://doi.org/10.22054/jcsm.2021.55657.1022

Abstract
  The aim of this paper is to learn a Bayesian network structure for discrete variables. For this purpose, we introduce a Gibbs sampler method. Each sample represents a Bayesian network. Thus, in the process of Gibbs sampling, we obtain a set of Bayesian networks. For achieving a single graph that represents ...  Read More

A Bayesian Semiparametric Random Effect Model for Meta-Regression

Ehsan Ormoz

Volume 1, Issue 2 , June 2023, , Pages 205-223

https://doi.org/10.22054/jcsm.2022.69925.1032

Abstract
  In this paper, we will introduce a Bayesian semiparametric model concerned with both constant and coefficients. In Meta-Analysis or Meta-Regression, we usually use a parametric family. However, lately the increasing tendency to use Bayesian nonparametric and semiparametric models, entered this area too. ...  Read More